Forensic image analysis using inconsistent noise pattern

With the advancement of image acquisition devices and social networking services, a huge volume of image data is generated. Using different image and video processing applications, these image data are manipulated, and thus, original images get tampered. These tampered images are the prime source of spreading fake news, defaming the personalities and in some cases (when used as evidence) misleading the law bodies. Hence before relying totally on the image data, the authenticity of the image must be verified. Works of the literature are reported for the verification of the authenticity of an image based on noise inconsistency. However, these works suffer from limitations of confusion between edges and noise, post-processing operation for localization and need of prior knowledge about an image. To handle these limitations, a noise inconsistency-based technique has been presented here to detect and localize a false region in an image. This work consists of three major steps of pre-processing, noise estimation and post-processing. For the experimental purpose two, publicly available datasets are used. The result is discussed in terms of precision, recall, accuracy and f1-score on the pixel level. The result of the presented work is also compared with the recent state-of-the-art techniques. The average accuracy of the proposed work on datasets is 91.70%, which is highest among state-of-the-art techniques.

     

Multi-Model Approach to Assess the Dynamics of Hydrologic Components in a Tropical Ecosystem

Estimation of terrestrial water budget at global and regional scales are essential for efficient agricultural water management, flood predictions, and, hydrological modeling. In hydrological modeling, it is a challenging task to quantify the major hydrological components like runoff, evapotranspiration (ET), and total water storage (TWS) due to improper and limited availability of detailed meteorological datasets. Furthermore, there has been no consensus to answer a-decade-long critical question that a less data-intensive models can be an alternate to robust data-intensive models in data scarce conditions. This study aims at multi-model approach over the single models usage for representing the hydrological behaviour in the Kangsabati River Basin (KRB), India. It is done by applying the standard model selection criteria over various hydrological models. Two hydrological models are selected, a semi- distributed model, Variable Infiltration Capacity (VIC-3 L), and a conceptually lumped model, Identification of unit Hydrograph and Component flows from Rainfall, Evapotranspiration and Streamflow (IHACRES). Both models were calibrated against the observed daily discharge at the KRB outlet for the period of 2001–2006 and validated for 2008–2010. The results show that both VIC-3 L and IHACRES produce reasonable runoff estimates at daily and monthly time scale in the KRB. The ET estimates show that VIC-3 L and IHACRES captured the seasonal variations with the percent change of 0.4% and 6.6% respectively. As IHACRES is simpler, parsimonious, fewer parameters, and better performances, it can be useful for hydrological modeling in data-scarce regions.

     

Hydrological Response to Agricultural Land Use Heterogeneity Using Variable Infiltration Capacity Model

Hydrological responses corresponding to the agricultural land use alterations are critical for planning crop management strategies, water resources management, and environmental evaluations. However, accurate estimation and evaluation of these hydrological responses are restricted by the limited availability of detailed crop classification in land use and land cover. An innovative approach using state-of-the-art Variable Infiltration Capacity (VIC) model is utilized by setting up the crop-specific vegetation parameterization and analyse the effect of uniform and heterogeneous agricultural land use over the hydrological responses of the basin, in the Kangsabati River Basin (KRB). Thirteen year simulations (1998–2010) based on two different scenarios i.e., single-crop in agricultural land use (SC-ALU) and multi-crop in agricultural land use (MC-ALU) patterns are incorporated in the model and calibrated (1998–2006) and validated (2007–2010) for the streamflow at Reservoir and Mohanpur in the KRB. The results demonstrated that the VIC model improved the estimates of hydrological components, especially surface runoff and evapotranspiration (ET) at daily and monthly timescales corresponding to MC-ALU than SC-ALU (NSC?>?0.7). Grid-scale ET estimates are improved after incorporating heterogeneous agricultural land use (NSC?>?0.55 and R²?>?0.55) throughout the period of 1998–2010. This study improves our understanding on how the change in agricultural land use in the model settings alters the basin hydrological characteristics, and to provide model-based approaches for best management practices in irrigation scheduling, crop water requirement, and management strategies in the absence of flux towers, eddy covariance, and lysimeters in the basin.

     

Modelling geometric and thermal errors in a five-axis cnc machine tool

The total volumetric error within the workspace of a machine tool is induced by the propagation of both scalar and position dependent geometrical errors, as well as time-variant thermal errors. This paper presents a compact volumetric error model which can be used as a basis for a practical compensation scheme. The broad objective is to increase the achievable accuracy of an industrial five-axis CNC machine tool. In place of using Denavit-Hartenberg (D-H) transformations, the method used here directly considers the shape and joint transformations for inaccurate links and joints using small angle approximations and then finds the total volumetric error in the workspace as a function of all the possible errors.The development of the model shows that angular deviations are independent of translational errors. However, the tool point deviations are dependent on both translational and rotational errors. The model has been used for the design and testing of a compensation strategy. The simulation studies indicate that CNC compensation for errors in X, Y and Z axes is possible. However, the capability of the CNC compensation for pitch, roll and yaw errors is dependent on the positioning of the rotary axes on the machine tool. This is shown by an example using the compensation scheme developed.     

Thermodynamic modeling and phase equilibria calculations of the quaternary Al-Ga-In-Sb Sastem

Quasi sub-subregular solution model with additional ternary parameters, used by Sharma et al. to model the thermodynamic properties of the liquid phases in the ternary Al-Ga-Sb, Al-In-Sb, and GaIn-Sb systems, has been extended to predict the thermodynamic properties of the liquid phase in the quaternary Al-Ga-In-Sb system. The (AlGaln)Sb compound phase in the quaternary Al-Ga-In-Sb system is considered a quasi-regular solution of AlSb, GaSb, and InSb compounds. Phase equilibria in the quaternary Al-Ga-In-Sb system are then calculated and compared with the limited experimental data available in the literature. The ternary Al-Ga-In phase diagram, required for the quaternary calculations, has also been modeled and calculated.     

Ferroelectric liquid crystals: Excellent tool for modern displays and photonics

The ferroelectric liquid crystals, because of their fast electro‐optical response, are one of the most important classes of liquid crystals. Here, in this review, we have summarized the different electro‐optical modes for ferroelectric liquid crystals. Clark–Lagerwall effect (surface stabilized ferroelectric liquid crystal), deformed helix ferroelectric (DHF) effect, electrically suppressed helix (ESH) mode, DHF orientational Kerr effect, and ESH diffraction modes have been discussed. All of the crucial features, that is, optics, electro‐optics, dynamics, and their dependence on material parameters, operational regime, and applications, have been reviewed.     

Reputation based probabilistic resource allocation for avoiding free riding and formation of common interest groups in unstructured P2P networks

Free riding is a major problem in peer-to-peer networks. Reputation management systems are generally employed to overcome this problem. In this paper, a new reputation based scheme called probabilistic resource allocation is proposed. This strategy probabilistically decide whether to provide the resource to requesting peer or not. Aforesaid method gives selection preference to higher reputation peers and at the same time provides some finite probability of interaction between those peers who don’t have good reputation about each other. This avoids disconnection between the aforesaid peers. The proposed scheme also introduces a new mechanism for resource distribution which not only allocates resources based on peers’ reputation but simultaneously maximizes network utility also. Algorithm for formation of interest groups based upon both similarity of interests and reputation between peers is also presented.     

Generic and efficient framework for search trees on flash memory storage systems

Tree index structures are crucial components in data management systems. Existing tree index structure are designed with the implicit assumption that the underlying external memory storage is the conventional magnetic hard disk drives. This assumption is going to be invalid soon, as flash memory storage is increasingly adopted as the main storage media in mobile devices, digital cameras, embedded sensors, and notebooks. Though it is direct and simple to port existing tree index structures on the flash memory storage, that direct approach does not consider the unique characteristics of flash memory, i.e., slow write operations, and erase-before-update property, which would result in a sub optimal performance. In this paper, we introduce FAST (i.e., Flash-Aware Search Trees) as a generic framework for flash-aware tree index structures. FAST distinguishes itself from all previous attempts of flash memory indexing in two aspects: (1) FAST is a generic framework that can be applied to a wide class of data partitioning tree structures including R-tree and its variants, and (2) FAST achieves both efficiency and durability of read and write flash operations through memory flushing and crash recovery techniques. Extensive experimental results, based on an actual implementation of FAST inside the GiST index structure in PostgreSQL, show that FAST achieves better performance than its competitors.     

Template-based program verification and program synthesis

Program verification is the task of automatically generating proofs for a program’s compliance with a given specification. Program synthesis is the task of automatically generating a program that meets a given specification. Both program verification and program synthesis can be viewed as search problems, for proofs and programs, respectively. For these search problems, we present approaches based on user-provided insights in the form of templates. Templates are hints about the syntactic forms of the invariants and programs, and help guide the search for solutions. We show how to reduce the template-based search problem to satisfiability solving, which permits the use of off-the-shelf solvers to efficiently explore the search space. Template-based approaches have allowed us to verify and synthesize programs outside the abilities of previous verifiers and synthesizers. Our approach can verify and synthesize difficult algorithmic textbook programs (e.g., sorting and dynamic programming-based algorithms) and difficult arithmetic programs.